Tiara: deep learning-based classification system for eukaryotic sequences.

ABSTRACT:

Motivation

With a large number of metagenomic datasets becoming available, eukaryotic metagenomics emerged as a new challenge. The proper classification of eukaryotic nuclear and organellar genomes is an essential step toward a better understanding of eukaryotic diversity.

Results

We developed Tiara, a deep-learning-based approach for the identification of eukaryotic sequences in the metagenomic datasets. Its two-step classification process enables the classification of nuclear and organellar eukaryotic fractions and subsequently divides organellar sequences into plastidial and mitochondrial. Using the test dataset, we have shown that Tiara performed similarly to EukRep for prokaryotes classification and outperformed it for eukaryotes classification with lower calculation ti

SUBMITTER: Karlicki M 

PROVIDER: S-EPMC8722755 | biostudies-literature | 2022 Jan

REPOSITORIES: biostudies-literature